Autonomic Computing Introduction, Motivations, Overview Manish - PDF document

Autonomic Computing Introduction, Motivations, Overview Manish Parashar The Applied Software Systems Laboratory Rutgers, The State University of New Jersey http://automate.rutgers.edu Salim Hariri High Performance Distributed Computing Laboratory The University of Arizona http://www.ece.arizona.edu/~hpdc ICAC 2004 Autonomic Computing Tutorial May 16, 2004 Tutorial Outline • Objectives – lay the foundations of Autonomic Computing – present the defining research issues, present the opportunities and challenges of Autonomic Computing – review the current landscape of Autonomic Computing – present an overview of AutoMate and Autonomia • More Information – http://www.autonomic-conference.org/tutorial/ – http://automate.rutgers.edu/ Autonomic Computing Tutorial, ICAC 2004 2 Autonomic Computing Tutorial, ICAC 2004 1

Agenda Autonomic Computing Tutorial, ICAC 2004 3 Emerging Information Infrastructures - Smaller/Cheaper/Faster/Powerful/Connected …. • Explosive growth in computation, communication, information and integration technologies – computing & communication is ubiquitous • Pervasive ad hoc “anytime-anywhere” access environments – ubiquitous access to information – peers capable of producing/consuming/processing information at different levels and granularities – embedded devices in clothes, phones, cars, mile-markers, traffic lights, lamp posts, medical instruments … • “On demand” computational/storage resources, services Autonomic Computing Tutorial, ICAC 2004 4 Autonomic Computing Tutorial, ICAC 2004 2

Faster/Smaller/Cheaper/Powerful/Connected …. Autonomic Computing Tutorial, ICAC 2004 5 Motivation: Complexity Directory Directory and Security Existing and Security Existing Dozens of Services Services Applications Applications systems and and Data and Data applications Business Business Data Data Data Data Server Server Web Web Thousands of Web DNS Web DNS Application Application Server Server Server Server Server Server tuning parameters Storage Area Storage Area Network Network Hundreds of components BPs and BPs and Data Data External External Services Services Autonomic Computing Tutorial, ICAC 2004 6 Autonomic Computing Tutorial, ICAC 2004 3

Motivation: Complexity • Individual system elements increasingly difficult to maintain and operate – 100s of config, tuning parameters for commercial databases, servers, storage • Heterogeneous systems are becoming increasingly connected – Integration becoming ever more difficult • Architects can't intricately plan component interactions – Increasingly dynamic; more frequently with unanticipated components • This places greater burden on system administrators, but they are already overtaxed – – they are already a major source of cost (6:1 for storage) and error • We need self-managing computing systems – Behavior specified by sys admins via high-level policies – System and its components figure out how to carry out policies Autonomic Computing Tutorial, ICAC 2004 7 Autonomic Computing Tutorial, ICAC 2004 8 Autonomic Computing Tutorial, ICAC 2004 4

Motivation: Increasing Cost Autonomic Computing Tutorial, ICAC 2004 9 Rapid Changes, I ncreased Complexity Autonomic Computing Tutorial, ICAC 2004 10 Autonomic Computing Tutorial, ICAC 2004 5

The bad news … • Unprecedented – scales, complexity, heterogeneity, dynamism and unpredictability, lack of guarantees • Millions of businesses, Trillions of devices, Millions of developers and users, Coordination and communication between them • The increasing system complexity is reaching a level beyond human ability to design, manage and secure – programming environments and infrastructure are becoming unmanageable, brittle and insecure • A fundamental change is required in how system and applications are formulated, constructed, composed and managed Autonomic Computing Tutorial, ICAC 2004 11 Convergence of Information Technology and Biology • Our system design methods and management tools seem to be inadequate for handling the complexity, size, and heterogeneity of today and future Information systems • Biological systems have evolved strategies to cope with dynamic, complex, highly uncertain constraints Autonomic Computing Tutorial, ICAC 2004 12 Autonomic Computing Tutorial, ICAC 2004 6

Adaptive Biological Systems • The body’s internal mechanisms continuously work together to maintain essential variables within physiological limits that define the viability zone • Two important observations: – The goal of the adaptive behavior is directly linked with the survivability – If the external or internal environment pushes the system outside its physiological equilibrium state the system will always work towards coming back to the original equilibrium state Autonomic Computing Tutorial, ICAC 2004 13 Ashby’s Ultrastable System • The Ashby Ultra-Stable system consists as two close loops: one that can control small disturbances while the second control loop is responsible for longer disturbances. Essential Variables Environment Motor Sensor channels channels Reacting Part R Step Mechanisms/Input Parameter S Autonomic Computing Tutorial, ICAC 2004 14 Autonomic Computing Tutorial, ICAC 2004 7

The Nervous System: A subsystem within Ashby’s Ultrastable System • The nervous system is divided into the Peripheral Nervous System (PNS) and the Central Nervous System (CNS) • CNS consists of two parts: sensory-somatic nervous system and the autonomic nervous system. Sensory neurons Sensory neurons Sensory – Autonomic Central Internal External Somatic Nervous nervous environment environment Nervous Sensor Channels System system (CNS) System Sensory Neurons Internal External Reacting Part R environment environment Motor neurons Motor neurons Motor Neurons Essential Variables Motor Channels (EV) Environment S = f (change in EV) Step Mechanisms/Input Parameter S Autonomic Computing Tutorial, ICAC 2004 15 Convergence of Information Technology and Biology Without requiring our conscious involvement - when we run, it increases our heart and breathing rate Autonomic Computing Tutorial, ICAC 2004 16 Autonomic Computing Tutorial, ICAC 2004 8

Autonomic Computing? • Nature has evolved to cope with scale, complexity, heterogeneity, dynamism and unpredictability, lack of guarantees – self configuring, self adapting, self optimizing, self healing, self protecting, highly decentralized, heterogeneous architectures that work !!! – e.g. the human body – the autonomic nervous system • tells you heart how fast to beat, checks your blood’s sugar and oxygen levels, and controls your pupils so the right amount of light reaches your eyes as you read these words, monitors your temperature and adjusts your blood flow and skin functions to keep it at 98.6ºF • coordinates - an increase in heart rate without a corresponding adjustment to breathing and blood pressure would be disastrous • is autonomic - you can make a mad dash for the train without having to calculate how much faster to breathe and pump your heart, or if you’ll need that little dose of adrenaline to make it through the doors before they close – can these strategies inspire solutions? • e.g. FlyPhones, AORO/AutoMate, ROC, ELiza, etc. – of course, there is a cost • lack of controllability, precision, guarantees, comprehensibility, … Autonomic Computing Tutorial, ICAC 2004 17 Autonomic Computing – The Next Era of Computing “ Computer Systems that can regulate themselves much in the same way as our autonomic nervous system regulates and protects our bodies.” (by Paul Horn, IBM) Autonomic Computing Tutorial, ICAC 2004 18 Autonomic Computing Tutorial, ICAC 2004 9

Autonomic Computing - The Vision “ increasing productivity while minimizing complexity for users… ” “ to design and build computing systems capable of running themselves, adjusting to varying circumstances, and preparing their resources to handle most efficiently the workloads we put upon them. “ Autonomic Computing Tutorial, ICAC 2004 19 By IBM PS: Its not AI • Does not require the duplication of conscious human thought as an ultimate goal. • Does require system to take over certain functions previously performed by humans Autonomic Computing Tutorial, ICAC 2004 20 By IBM Autonomic Computing Tutorial, ICAC 2004 10

Autonomic Computing Characteristics (IBM) • 1. Self Defining – To be autonomic, a computing system needs to know itself and comprise components – It needs detail knowledge of its components, current state, ultimate capacity – It needs to know all the connections to other systems to govern itself – It needs to know ownership level, from whom it can borrow resources, share or not to share, etc. Autonomic Computing Tutorial, ICAC 2004 21 Autonomic Computing Characteristics (IBM) Autonomic Computing Tutorial, ICAC 2004 22 By IBM Autonomic Computing Tutorial, ICAC 2004 11